Bibliographic record
Abstract
I argue that the Supreme Court of Canada's analytical framework for assessing social science evidence in its proportionality analysis is inadequate with respect to democratic rights and freedoms. The article addresses the limits to the use of social science evidence in cases engaging s. 3 and s. 2(b) of the Charter of Rights and Freedoms. The article then identifies and critiques the Supreme Court's existing approach to social science evidence in its proportionality analysis in cases involving democratic rights and freedoms. I argue that the jurisprudence permits a highly deferential approach to the state's justification for infringing democratic rights and freedoms. This approach is inappropriate given the risk of partisan self-dealing by incumbents and in conflict with the Court's jurisprudence identifying democratic rights as fundamental or core rights entitled to the highest level of protection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.082 | 0.181 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.013 | 0.097 |
| Scholarly communication | 0.025 | 0.023 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".